logistic model
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2022 ◽  
Author(s):  
David H Roberts

We apply the simple logistic model to the four waves of COVID-19 taking place in South Africa over the period 2020~January~1 through 2022 January 11. We show that this model provides an excellent fit to the time history of three of the four waves. We then derive a theoretical correlation between the growth rate of each wave and its duration, and demonstrate that it is well obeyed by the South Africa data. We then turn to the data for the United States. As shown by Roberts (2020a, 2020b), the basic logistic model provides only a marginal fit to the early data. Here we break the data into six "waves," and treat each one separately. For four of the six the logistic model is useful, and we present full results. We then ask if these data provide a way to predict the length of the ongoing Omicron wave in the US (commonly called "wave 4," but the sixth wave as we have broken the data up). Comparison of these data to those from South Arica, and internal comparison of the US data, suggests that this last wave will die out by about 2022-January-20.


Author(s):  
Yehui Tong ◽  
Ramon Saladrigues

Using the logistic model, this article investigates the influence of financial factors on gaining profits for new firms in the Spanish food industry. Specifically, the firms founded separately during the crisis period and during the postcrisis period are observed for their first three years. The findings suggest that indebtedness (for both periods), previous profitability (for the postcrisis period) and accounts payable (for the crisis period) were most frequently statistically significant in the logistic model. Hence, for new firms, controlling debt burden, accumulating internally generated funds and using payables to establish business relationships can help to gain profits. Firm size and asset rotation were significant in the first year (especially during the postcrisis period), with a positive relationship to profits. Given that the food industry is highly competitive, enlarging firm size to reach efficiencies of scale and using a low-price strategy with high asset rotation to obtain market share are effective marketing strategies for new firms. This article contributes to the empirical studies about the financial effects on new firms' profits in the food industry; it can also help potential entrepreneurs make better decisions about starting new businesses and help to manage new firms better in different macroeconomic environments.


2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Maotao Lai

With the further development of China's market economy, the competition faced by companies in the market has become more intense, and many companies have difficulty facing pressure and risks. Among the many types of enterprises, high-tech enterprises are the riskiest. The emergence of big data technologies and concepts in recent years has provided new opportunities for financial crisis early warning. Through in-depth study of the theoretical feasibility and practical value of big data indicators, the use of big data indicators to develop an early warning system for financial crises has important theoretical value for breaking through the stagnant predicament of financial crisis early warning. As a result of the preceding context, this research focuses on the influence of big data on the financial crisis early warning model, selects and quantifies the big data indicators and financial indicators, designs the financial crisis early warning model, and verifies its accuracy. The specific research design ideas include the following: (1) We make preliminary preparations for model construction. Preliminary determination and screening of training samples and early warning indicators are carried out, the samples needed to build the model and the early warning indicator system are determined, and the principles of the model methods used are briefly described. First, we perform a significant analysis of financial indicators and screen out early warning indicators that can clearly distinguish between financial crisis companies and nonfinancial crisis companies. (2) We analyze the sentiment tendency of the stock bar comment data to obtain big data indicators. Then, we establish a logistic model based on pure financial indicators and a logistic model that introduces big data indicators. Finally, the two models are tested and compared, the changes in the model's early warning effect before and after the introduction of big data indicators are analyzed, and the optimization effect of big data indicators on financial crisis early warning is tested.


2022 ◽  
pp. 001316442110634
Author(s):  
Patrick D. Manapat ◽  
Michael C. Edwards

When fitting unidimensional item response theory (IRT) models, the population distribution of the latent trait (θ) is often assumed to be normally distributed. However, some psychological theories would suggest a nonnormal θ. For example, some clinical traits (e.g., alcoholism, depression) are believed to follow a positively skewed distribution where the construct is low for most people, medium for some, and high for few. Failure to account for nonnormality may compromise the validity of inferences and conclusions. Although corrections have been developed to account for nonnormality, these methods can be computationally intensive and have not yet been widely adopted. Previous research has recommended implementing nonnormality corrections when θ is not “approximately normal.” This research focused on examining how far θ can deviate from normal before the normality assumption becomes untenable. Specifically, our goal was to identify the type(s) and degree(s) of nonnormality that result in unacceptable parameter recovery for the graded response model (GRM) and 2-parameter logistic model (2PLM).


2022 ◽  
Vol 11 ◽  
Author(s):  
Zijun Guo ◽  
Lingjun Meng ◽  
Shuxin Tian ◽  
Lan Chen ◽  
Huiying Shi ◽  
...  

BackgroundLugol chromoendoscopy (LCE) is a technique that is inexpensive and convenient for screening esophageal neoplastic lesions. However, the specificity of LCE is limited. The purpose of this study was to determine the risk characteristics of lesions related to false-positive results for LCE.MethodsIn this retrospective study, 871 lesions in 773 patients scheduled for LCE in Wuhan Union Hospital and First Affiliated Hospital of Shihezi University between April 2013 and October 2018 were enrolled. The 871 lesions were used to determine the diagnostic performance of LCE for detecting esophageal neoplastic lesions and were divided into an LCE-positive group (627 lesions) and an LCE-negative group (244 lesions). Six hundred and twenty-seven unstained/understained lesions from 563 patients were used to determine the significant risk factors for misdiagnosis of neoplasms by LCE. Among them, 358 lesions and 269 lesions were classified into the misdiagnosed group and correctly diagnosed group, respectively. A multivariate logistic regression analysis was conducted for suspected esophageal neoplastic lesions during the LCE examination.ResultsThe sensitivity, specificity, and overall accuracy for LCE were 100%, 40.5%, and 58.9%, respectively. Among 13 characteristics of lesions, lesions with branching vascular network (OR 4.53, 95% CI 2.23–9.21, p < 0.001), smooth lesions (OR 2.40, 95% CI 1.38–4.18, p = 0.002) under white light endoscopy (WLE), lesions with a size < 5 mm (OR 3.06, 95% CI 1.38–6.78, p = 0.006), ill-demarcated lesions (OR 7.83, 95% CI 4.59–13.37, p < 0.001), and pink color sign (PCS)-negative (OR 4.04, 95% CI 2.38–6.84, p < 0.001) lesions after reaction with iodine solution were independent risk factors for misdiagnosis as neoplastic lesions by LCE.ConclusionLCE has a high sensitivity but limited specificity for screening esophageal neoplastic lesions. For unstained or understained lesions, branching vascular network or smooth appearance under WLE, a size < 5 mm in diameter, ill-demarcated, or PCS-negative lesions after staining are related to the misdiagnosis of esophageal neoplastic lesions by LCE based on logistic regression. The multivariate logistic model may be used to predict the possibility of misdiagnosis and help improve the specificity of LCE in diagnosing esophageal neoplastic lesions.


2022 ◽  
Vol 12 (1) ◽  
pp. 168
Author(s):  
Eisa Abdul-Wahhab Al-Tarawnah ◽  
Mariam Al-Qahtani

This study aims to compare the effect of test length on the degree of ability parameter estimation in the two-parameter and three-parameter logistic models, using the Bayesian method of expected prior mode and maximum likelihood. The experimental approach is followed, using the Monte Carlo method of simulation. The study population consists of all subjects with the specified ability level. The study includes random samples of subjects and of items. Results reveal that estimation accuracy of the ability parameter in the two-parameter logistic model according to the maximum likelihood method and the Bayesian method increases with the increase in the number of test items. Results also show that with long and average length tests, the effectiveness is related to the maximum likelihood method and to all conditions of the sample size, whereas in short tests, the Bayesian method of prior mode outperformed in all conditions. Results indicate that the increase of the ability parameter in the three-parameter logistic model increases with the increase of test items number. The Bayesian method outperforms with respect to the accuracy of estimation at all conditions of the sample size, whereas in long tests the maximum likelihood method outperforms at all different conditions.   Received: 17 September 2021 / Accepted: 24 November 2021 / Published: 3 January 2022


In this work, through a logistic model, several aspects of organizations are related, such as ethics, Safety & Security and innovation. To do this, the Ethical Legal Consultant of the Logistic Model Based on Positions will be used. Given the close relationship that logistics has with almost all aspects of the organization, the objective of this work arises: Generate some guidelines to improve the ethical aspects of an organization, following guidelines offered by the Legal Ethical Consultant of the Logistics Model Based on Positions. To achieve this objective, the Integrated-Adaptable Methodology for the development of Decision Support System will be followed, which, it has been demonstrated, adapts to this type of research.


2021 ◽  
Vol 5 (3) ◽  
pp. 1-8
Author(s):  
Chuks ONYEKA IDIAYE ◽  
Isaac BUSAYO OLUWATAYO ◽  
Taiwo OLUWASEUN DISU

The objective of this study was to investigate the extent and perception of contraceptive use among women from farming households in Oyo state, Nigeria. Descriptive statistics were used in profiling the socioeconomic characteristics of respondents, a multinomial logistic model was used to estimate the determinants of contraceptive usage, while the Likert scale was used to measure their perception towards the use of contraceptives. A total of 150 women were interviewed using a structured questionnaire. The results obtained indicated that while only 27% of the women were aware of contraceptives, 23% of them had used them. Cost was the most important consideration among the women for choosing a method as indicated by 41% of them. Further, among those who had not used any contraceptive, traditional and religious beliefs were their major considerations. The regression analysis showed formal education to be a significant factor (at α0.05) that increased the probability of women embracing contraception. Perception towards contraceptives among women in rural Oyo State, Nigeria was seen to be generally positive, although convenience of the methods (mean score 1.49) and side effects (means score 1.35) were considered to be drawbacks. It was recommended that more awareness needed to be created on birth control along with the introduction of modern methods of contraception with fewer side effects. Also, family planning interventions in Nigeria should be made context-specific and culturally appealing so as to increase their acceptability in rural farming communities.


2021 ◽  
Vol 12 (23) ◽  
pp. 1-25
Author(s):  
Niranjan Devkota ◽  
Udaya Raj Poudel ◽  
Iveta Hamarneh ◽  
Udbodh Bhandari

The impacts of westernization are increasing globally in the tourism entrepreneurship practices. Understanding it contributes to the growth and sustainability of the business even in local touristic cities. This paper aims to judge tourists’ perception of westernization about one of the most important touristic cities – Pokhara, Nepal. Purposive sampling was used to collect responses from 248 tourists in Pokhara, which included both open and closed-ended questionnaires. In order to understand the perception of tourists and check the determinants about the prevalence of westernization among tourists, the cross-sectional descriptive study has been used, and Logit Regression Model is applied. The study reveals that 78.22% of the respondents find westernization has influenced tourism entrepreneurship up to a certain extent in Pokhara. Similarly, a majority (89.11%) of tourists reveal that they expect and enjoy local culture than their own culture in tourism destinations, where 95.56% of the tourists suggest preserving the local culture for the sustainability of tourism business in Pokhara. Results from the Ordered Logistic model show that westernization, problems faced in destination, the similarity of destination as per their expectation and level of tourists’ existence at destination play significant roles in their preferences to visit touristic destinations. This study indicates that the first two reduce tourists’ preferences while the latter two stimulate their preferences to visit Pokhara, Nepal. Therefore, entrepreneurs in Pokhara should identify, conserve, encourage, and maintain local socio-cultural traditions to have long-term tourism prosperity and development.


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